In signal processing systems, there is often a need to compensate for nonlinear distortions introduced by the system. There are many possible sources for system nonlinearities, including characteristics of nonlinear components such as inductors, capacitors and transistors. Nonlinearities are frequently introduced when analog signals are converted to digital. Besides component nonlinearities, analog-to-digital converters (ADCs) often have additional sources of nonlinearity, such as the sampling capacitors' time constants, gain error in amplifiers and imprecision in the comparator levels.
Nonlinear distortions may depend on many factors such as the input signal's frequency range, history and rate of change (also referred to “slew rate”), as well as external factors such as operating temperature. The difficulties in modeling nonlinear distortions lead to difficulties in characterizing and compensating system nonlinearities. Existing techniques for characterizing system nonlinearities such as Volterra expansion tend to be complex and difficult to implement.
Furthermore, in some systems, even if a distortion model is found by using Volterra expansion, it could not be accurately applied due to the unavailability of the required inputs. For example, in some communication systems, the receiver circuitry may introduce nonlinearities when the input analog signal is digitized and demodulated to baseband. The intermediate frequency (IF) signal required by the distortion model is often unavailable since the IF signal is directly demodulated to baseband when the ADC samples the signal. Applying the baseband signal to the distortion model usually means that some of the history and slew rate information is lost; therefore, the distortion estimation is less accurate.
It would be useful to have a way to better compensate for system nonlinearities even as some of the data required by the distortion model is not available as input. It would also be useful if the compensation scheme could be applied without requiring special data access.